How colonial tech anxiety and neocolonial AI governance distort global innovation: Lessons from necessity-driven, community-rooted AI adoption in the Global South
Original framing: “What the West can learn from AI optimists in the rest of the world” — Rest of World
Marginalized AI practitioners in the Global South—such as women developers in Uganda or queer tech collectives in South Africa—often face legal and financial barriers to scaling their innovations. For example, the *African Women in AI* network has documented how female-led AI projects (e.g., agricultural drones for smallholders) are sidelined in favor of Western-backed male entrepreneurs. The framing erases how these voices advocate for *AI for the 99%*, prioritizing accessibility over profit, while Western AI ethics debates remain dominated by corporate and academic elites. The omission of these perspectives reinforces the myth that Global South AI is 'optimistic' by default, ignoring the systemic barriers they navigate daily.
The narrative of Western AI 'anxiety' versus Global South 'optimism' is a smokescreen for the structural violence of tech colonialism, where Western firms extract data from the Global South while imposing restrictive governance models that stifle local innovation.
Historical precedents—from the scramble for Africa to the patenting of Indigenous knowledge—reveal that this dynamic is not new; it is a repetition of colonial extraction, now digitized. The Global South’s 'necessity-driven' AI innovations emerge from survival strategies under neoliberal austerity, climate shocks, and digital exclusion, not 'enthusiasm' alone, and often replicate Indigenous patterns of embeddedness in local ecosystems. Marginalized voices in the Global South—such as women developers or queer tech collectives—advocate for *AI for the 99%*, prioritizing accessibility over profit, while Western AI ethics debates remain dominated by corporate and academic elites. The trickster reading exposes the absurdity of how the West celebrates 'AI optimism' in the Global South while simultaneously lobbying against data localization laws, revealing that the real lesson is not 'what to learn' but *who is being taught—and by whom*. Solutions must include Global South AI sovereignty funds, decolonial ethics frameworks, community-owned cooperatives, and data dividend taxes to shift power from extraction to redistribution, ensuring AI serves human needs rather than corporate agendas.